Reverse Dependencies of nibabel

The following projects have a declared dependency on nibabel:

• nnunet — nnU-Net. Framework for out-of-the box biomedical image segmentation.
• nnunet-customized — nnU-Net. Framework for out-of-the box biomedical image segmentation.
• nnunet-inference-on-cpu-and-gpu — nnU-Net. Framework for out-of-the box biomedical image segmentation. Can do inference on both gpu(if cuda available) and cpu(if cuda not available)
• nnunetv2 — nnU-Net is a framework for out-of-the box image segmentation.
• nnunetv2-bm-custom — nnU-Net is a framework for out-of-the box image segmentation.
• nobrainer — A framework for developing neural network models for 3D image processing.
• novas3d — no summary
• nsdcode — NSD map data from various spaces
• nuclearowl — A lib handling nuclear imaging data and Ai applications on top of it
• numex — A quick-and-easy explorer for numerical data.
• nxbc — NX Bias Correction. NIfTI image bias correction, implementation of N3 (Sled) and N4 (Tustison) algorithms
• oct-tissuemasking — A PyTorch based package for automated OCT tissue masking.
• oct-vesselseg — A Label-Free and Data-Free Synthesis Engine and Training Framework for Vascular Segmentation of sOCT Data with PyTorch.
• onevox — Library for adding well described noise to images.
• optimed — Optimed
• orcaz — ORCA (Optimized Registration through Conditional Adversarial networks)
• ormir-pyvoxel — I/O routines for medical imaging data
• osl-dynamics — Models for infering dynamics in neuroimaging data
• own-knowledge-gpt — Custom Knowledge GPT
• p-mod-api — Propelwise Modules
• p2022 — Propelwise Modules
• p2t2 — no summary
• panpipelines — MRI Processing Pipelines for PAN Healthy Minds for Life Study
• parspin — A toolbox in support of Markello et al., 2020
• patch-denoise — Denoising method for sequence of images or volumes. Primarly targeting fMRI data.
• pattools — Toolkit for neuro-imaging data manipulation and automation
• pcarpet — pcarpet: create a carpet plot from fMRI data and decompose it with PCA.
• pdfcompare — A Python package to compare files (PDF, docx, images) and generate reports in txt, html, or PDF format
• petprep-extract-tacs — PETPrep Extract Time Activity Curves Workflow
• petprep-hmc — PETPrep Head Motion Correction Workflow
• pettobids — A python implementation of an ECAT to BIDS converter.
• pfc-toolkit — The Precomputed Functional Connectome Toolkit
• pfdo-mgz2image — Runs mgz2image on each nested dir of an inputdir
• phas — PICSL Histology Annotation Server (PHAS)
• phase_unwrap — A simple, laplacian-based unwrapping pipeline for MRI phase images in Python.
• phybers — Phybers: A Package for Brain Tractography Analysis.
• phys2cvr — Python library to generate regressors for and compute Cerebrovascular Reactivity and lag maps.
• picachooser — Lightweight GUI for sorting, classifying, and matching MELODIC ICA components.
• pilab-regis — Implementation of regis
• pinr — Python tools for Interoperable Neuromorphometry Reporting
• pipetography — Pre/Post-processing pipeline for tractography wrapped around nipype and mrtrix3
• pkg-try-19-mb — A basic hello package
• popeye — popeye : voxel population receptive fields from fMRI data
• populse-mia — populse_mia
• prfsim — A free & open source python tool for population receptive field simulation of fMRI data.
• protocol — generic framework to develop protocols with implementations in neuroscience
• psmoe — A simple module for prostate segmentation of T2-W MRI sequences in Nifti format
• pumaz — PUMA (PET Universal Multi-tracer Aligner) is a robust and efficient tool for aligning images from different PET tracers. It leverages advanced diffeomorphic imaging techniques to offer high-precision alignment for multiplexed tracer images. PUMA aims to significantly enhance the accuracy and reproducibility of PET image studies.
• pyalfe — no summary
• PyBASC — A bootstrapping clustering algorithm for Python
• pybids — bids: interface with datasets conforming to BIDS
• pybids-reports — pybids-reports: report generator for BIDS datasets
• pyblm — The Big Linear Models Toolbox
• pyblmm — The Big Linear Mixed Models Toolbox
• pyBruker — Python Bruker Raw Data Handler
• pycad-medic — A medical imaging library for Python
• pydactim — A library to post-process MRI data
• PyDesigner-DWI — Python Port of NYU's Designer pipeline for dMRI processing
• PyDicomGrouping-Linux — A Python Toolbox for handing medical dicoms
• PyDicomGrouping-Mac — A Python Toolbox for handing medical dicoms
• PyDicomGrouping-Win — A Python Toolbox for handing medical dicoms
• pydra-mriqc — Pydra tasks package for mriqc
• pydra-nireports — Pydra tasks package for nireports
• pydra-niworkflows — Pydra tasks package for niworkflows
• PyDWI — Fast ADC and DKI maps
• pyfus-lib — Open source framework for functional ultrasound imaging data analysis
• PyHySCO — Pytorch toolbox for Hyperelastic Susceptibility Artifact Correction
• pymaia-learn — Python Package to support Deep Learning data preparation, pre-processing. training, result visualization and model deployment across different frameworks (nnUNet, nnDetection, MONAI).
• pymedio — read arbitrary medical images in python
• pymirc — Python imaging utilities developed in the medical imaging research center of KU Leuven
• pymrt — Python Magnetic Resonace Tools
• PyMVPA — Multivariate Pattern Analysis in Python
• PyMVPD — A python package for multivariate pattern dependence
• PyMVPD-LITE — A python package for multivariate pattern dependence
• pynemaiqpet — Analysis of PET NEMA IQ phantom scans
• pynibs — A python toolbox to conduct non-invasive brain stimulation (NIBS) experiments.
• pynipt-plugin-uncch-core — UNCCH core module for rsfMRI analysis - pynipt plugin
• PyNIT — Python NeuroImaging Toolkit
• pypet2bids — A python library for converting PET imaging and blood data to BIDS.
• pypmi — pypmi is a Python toolbox for working with data from the Parkinson's Progression Markers Initiative (PPMI)
• pyraug — Data Augmentation with VAE
• PySiTK — Python SimpleITK/WrapITK helper scripts
• pyslicetime — Python Slice Timing Correction
• pySPFM — A python package for Paradigm Free Mapping (3dPFM and 3dMEPFM).
• pysurfer — PySurfer: cortical surface visualization using Python.
• python-pySAP — PYthon Sparse data Analysis Package
• python3-utils-tdinoto — Useful wrapper functions for the most common python data types, and for nifti/dicom arrays.
• pytomography — Package to perform tomographic image reconstruction
• pyunc — Classes for reading UNC format MRI files
• pyvoxel — An AI-powered open-source medical image analysis toolbox
• pyVoxelStats — Python implementation of the VoxelStats toolbox for neuroimage analysis
• QbiPy — DCE-MRI analysis code from the QBI lab, University of Manchester
• qim3d — QIM tools and user interfaces for volumetric imaging
• qlayers — Quantitative layer analysis for renal MRI
• qmenta-anon — The qmenta-anon library is used to anonymize files before transferring them to the QMENTA platform.
• qsmxt — no summary
• quantiphyse — Quantiphyse is a data viewer and analysis platform for volumetric medical imaging data
• quickshear — Quickshear Defacing for Neuroimages
• rabies — RABIES: Rodent Automated Bold Improvement of EPI Sequences.
• raclahe — Original package to support Region Adaptive Magnetic Resonance Image Enhancement for improving CNN based segmentation of the prostate and prostatic zones paper